Data Center Market to Reach $1.8 Trillion by 2035

Data is driving transformation in every sector, from finance to space exploration. But to turn data into real business outcomes, you need hybrid compute that is AI-optimized, secure by design, and built for agility from edge to cloud. smc.int.hpe.com/s/e2e31

If 83% of your data lives on-prem, why send your AI workloads to the cloud? With reasoning workloads skyrocketing by 320x, routing everything through the cloud creates massive latency and cost bottlenecks for enterprises. The most sustainable approach is bringing AI directly to where your data already lives — and Dell Technologies is building the exact infrastructure to make that seamless. Check out this great breakdown from Jeff Clarke on how we are helping organizations bring AI agents safely on-prem: 👇 #DellTechWorld #AgenticAI #EnterpriseInfrastructure #DataGravity #OnPremAI #DellTechnologies #IWork4Dell

A new survey report uncovering how enterprises are simplifying their infrastructure, scaling cloud workloads, managing energy demands, and closing the AI skills gap. Key findings from the report: 🗞️ 97% say cloud platforms are critical to scaling AI  93% are optimizing infrastructure for energy efficiency  83% have already seen measurable ROI from their AI infrastructure investments  38% of top performers simplified their stack to accelerate time-to-value

The CFO wants lower cost. The CTO wants more power. Most cloud platforms force you to compromise between the two. 😅 Because traditional cloud infrastructure was built for shared workloads, not AI at scale. So as training jobs grow, data moves farther, latency increases, and costs start compounding through bandwidth, congestion, and egress fees. The CTO sees inconsistent training times and throughput bottlenecks. The CFO sees unpredictable cloud bills. CloudLogics changes the architecture itself. The Fastest Cloud for AI Workloads brings high-performance compute closer to where data already lives using dedicated infrastructure and private dark fiber engineered for deterministic performance. ☁️ #AIInfrastructure #CloudComputing #AIWorkloads

There's been a long-running assumption that the cloud won the infrastructure conversation. What's becoming clearer is that the story is still unfolding, especially as AI pushes new demands on compute, storage, and data movement. The same forces that drove everything to the cloud are now exposing where different approaches fit best. As workloads become more intensive and continuous, decisions around where compute lives start to tie directly to performance, cost control, and data ownership. In high-performance and AI-driven environments, infrastructure becomes less about a single destination and more about placing the right capability where it delivers the most impact.

Intelligence at scale demands infrastructure equal to the ambition behind it. We architect the core: sovereign cloud foundations, AI systems built for enterprise demands, and the engineering precision that turns acceleration into impact. #ProgressContinues

Egress costs quietly shape infrastructure decisions. Teams often design around where data can move cheaply, not where the workload should actually run. That is why BHK Cloud talks about zero-egress zones, regional pinning, and direct access between BHK S3 datasets and GPU clusters. The goal is straightforward: keep sensitive data in place, stream it to compute when needed, and avoid redundant caching or unnecessary movement. For AI, media, backups, and analytics, predictable data movement can be just as important as raw compute. If bandwidth and storage architecture are becoming a bottleneck, let’s talk through the workload. https://lnkd.in/d9i3qnpJ #CloudInfrastructure #DataMovement #GPUComputing #S3Storage #AIWorkloads

☁️ Twenty years ago, cloud promised freedom. Today, it raises a different question: ❓ Who controls the infrastructure your organisation depends on? As AWS celebrates its recent 20th anniversary, cloud computing finds itself at a fascinating crossroads. The conversation has moved well beyond scalability, agility and cost savings. 🤖 AI is driving unprecedented demand for compute. 🌍 Governments are increasingly focused on digital sovereignty. 🔒 Regulators are scrutinising data residency, jurisdiction and control. ⚖️ Boards are weighing innovation against resilience and concentration risk. Recent developments in Europe, alongside similar discussions in Canada and elsewhere, suggest that cloud is no longer viewed solely as a technology platform. Increasingly, it is being treated as strategic infrastructure. In our latest article, Cloud at 20: The New Battle for Digital Sovereignty, we explore how the cloud market has evolved over the past two decades and why the next era may be defined less by scale, and more by sovereignty, resilience and choice. Will digital sovereignty become one of the defining cloud challenges of the next decade? https://lnkd.in/eXvR2V_t #CloudComputing #DigitalSovereignty #CloudStrategy #CIO #CTO #AI #HybridCloud #TechnologyLeadership #DigitalTransformation

As AI reshapes cloud computing, legacy providers are struggling to keep up. New demands around density, cooling, and energy are rewriting the rules. Nscale’s Nidhi Chappell says the company is built for this shift—embracing new designs and operations to meet evolving needs and create a more resilient, future-ready model. Details in our latest s+b interview here: https://lnkd.in/efh9Zh6Z

Can Colombia’s internet infrastructure keep pace with the global AI boom? 🇨🇴🤖 In our latest report, Lead Industry Analyst Mike Dano breaks down Colombia's physical delivery layer, regional cloud latency benchmarks, and how local providers are adapting to support real-time AI workloads. 📉🌐 Read the full analysis here: https://lnkd.in/gBdGMrx6